nm000259
Speier et al. 2017 — A comparison of stimulus types in online classification of the P300 speller using language models
EEG
This dataset contains EEG recordings from 10 healthy adults performing a P300 speller task using a 6x6 character matrix, under two stimulus conditions (Famous Faces overlay and Inverting). Data were collected across two sessions per subject with three runs each, using a 32-channel g.tec EEG system at 256 Hz. The dataset is a BIDS-formatted derivative generated via MOABB from the original data reported in Speier et al. (2017), which compared classification approaches for the P300 speller using language models.
- Participants
- 10
- Channels
- 32 (10-10)
- Citations
- 28
- HED
- v8.4.0
- Size
- 773 MB
- Version
- v1.0.4
- Updated
- Aug 20, 2026